{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ***Introduction to Radar Using Python and MATLAB***\n",
    "## Andy Harrison - Copyright (C) 2019 Artech House\n",
    "<br/>\n",
    "\n",
    "# Power Density\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The power density at a target at a given distance is expressed as (Equation 4.22)\n",
    "\n",
    "$$\n",
    "P_d = \\frac{P_{in}\\,G(\\theta,\\phi)}{4 \\pi r^2} \\hspace{0.5in} \\text{(W/m}^2\\text{)}\n",
    "$$\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Begin by getting the library path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import lib_path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set the target minimum and maximum range (m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "target_min_range = 1e3\n",
    "\n",
    "target_max_range = 10e3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the `linspace` routine from `scipy` for the target range array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy import linspace\n",
    "\n",
    "target_range = linspace(target_min_range, target_max_range, 2000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set the radar antenna gain (dB) and peak power (W)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "antenna_gain = 10.0\n",
    "\n",
    "peak_power = 50e3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up the keyword args"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "kwargs = {'target_range': target_range,\n",
    "\n",
    "          'peak_power': peak_power,\n",
    "\n",
    "          'antenna_gain': 10.0 ** (antenna_gain / 10.0)}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the `power_density` routine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from Libs.radar_range.radar_range import power_density"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculate the power density at the target (W/m^2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd = power_density(**kwargs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the `matplotlib` routines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set the figure size\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = (15, 10)\n",
    "\n",
    "\n",
    "# Display the results\n",
    "\n",
    "plt.plot(target_range / 1.0e3, pd)\n",
    "\n",
    "\n",
    " # Set the plot title and labels\n",
    "\n",
    "plt.title('Power Density at the Target', size=14)\n",
    "\n",
    "plt.xlabel('Target Range (km)', size=12)\n",
    "\n",
    "plt.ylabel('Power Density (W/m$^2$)', size=12)\n",
    "\n",
    "\n",
    " # Set the tick label size\n",
    "\n",
    "plt.tick_params(labelsize=12)\n",
    "\n",
    "\n",
    "# Turn on the grid\n",
    "\n",
    "plt.grid(linestyle=':', linewidth=0.5)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
